In present practice, mobile devices take an increasingly prominent role in conducting various business transactions, and are increasingly preferred as a device for facilitating capture and submission of data necessary to conduct the corresponding business transaction. In many approaches, capture and submission involves the imaging of one or more documents, processing the image to extract necessary data therefrom, and submitting the data to a workflow configured to conduct/complete the business transaction using the data.
However, in many instances the captured image data are insufficient to allow extraction of the necessary data. For example the image may be of insufficient quality (e.g. text or symbols are obscured) due to blur, insufficient/improper lighting, perspective distortion, and other similar challenges unique to image capture using a mobile device (e.g. as opposed to a traditional flat-bed scanner or multifunction peripheral).
For this reason, most conventional image processing techniques attempt to ensure adequate image quality pre-capture and/or improve image quality post-capture to facilitate the extraction process. However, some images are simply insufficient for accurate, reliable data extraction.
Even under circumstances where the image quality is adequate or superior, certain types of documents do not lend to facile data extraction, e.g. where a document depicts a particularly complex background with data of interest (e.g. text, symbols) overlayed thereon, or depicts data of interest overlaying or in proximity to a background texture having similar optical characteristics (e.g. color, intensity, etc.) as the data of interest. In each of these situations, it may be impossible to accurately extract some or all of the data of interest.
Certain approaches, including those disclosed in U.S. Pat. No. 8,345,981, from which this application claims priority, address the above challenge via validation techniques that verify extracted data using information obtained from a document complementary to the imaged document. Exemplary complementary documents include an invoice and a purchase order, proof of delivery, quote, etc.
While the above validation techniques are reliable and advantageously produce highly accurate extraction results (including correcting errors in initial extraction attempts), the reliance on complementary documents presents a limitation in that the validation engine/technique must have access to complementary information, requiring storage, indexing, etc. thereof and consuming computational resources to obtain and locate necessary complementary information and perform the required comparison. In practical terms, this means the user must either manually or otherwise (e.g. via image-based data extraction) enter the “reference” information prior to comparison.
While pervasive data connections prevalent today obviate the need to store this potentially copious reference information directly on a mobile device, the mobile device must make a connection to a remote resource hosting the reference information if not stored locally. Accordingly, document-based validation techniques, while reliable and suitable for accomplishing the desired extraction accuracy and reliability, have a tendency to introduce additional time and cost to the validation process.
Therefore, there is a current need for an improved method of automatic business transaction document validation using mobile devices without relying on complementary documents or remote resources as a source of reference information.